EDP Sciences 1773022945 20260309 fre

laboutique.edpsciences.fr-R002814 03 01 01 R002814 00 ED E107 00 01 01 Mathematical Statistics 01 eng 08 336 03 22 57387645 17 01 P15 EDP Sciences & Science Press 01 01 P15 EDP Sciences & Science Press 11 00 20260203 02 01 002995 03 9782759839490 15 9782759839490 03 01 D1 EDP Sciences 45 03 laboutique.edpsciences.fr-002995 03 01 01 002995 03 9782759839490 15 9782759839490 10 EA E107 10 00 01 R002814 ED E107 1 10 01 02 Textbooks for Tomorrow's Scientists Textbooks for Tomorrow’s Scientists introduces advanced textbooks ona wide range of topics in STM subject areas. These books offer students,researchers, faculty and professionals the resources they need to learn andsucceed in graduate courses. 01 01 Mathematical Statistics 1 A01 01 A2426 Guoliang TIAN TIAN, Guoliang Guoliang TIAN <p>Dr. Guoliang TIAN is a Full Professor in the Department of Statistics and Data Science at SUSTech, specializing in mathematical statistics, likelihood inference, and data science, with 18 years of teaching experience at HKU and SUSTech.&nbsp;</p><div><br></div> <p>Dr. Guoliang TIAN is a Full Professor in the Department of Statistics and Data Science at SUSTech, specializing in mathematical statistics, likelihood inference, and data science, with 18 years of teaching experience at HKU and SUSTech.&nbsp;</p><p>Dr. Xuejun JIANG is an Associate Professor in the Department of Statistics and Data Science at SUSTech, specializing in mathematical statistics, likelihood inference, and data science.</p><div><br></div> 2 A01 01 A2427 Xuejun JIANG JIANG, Xuejun Xuejun JIANG <p>Dr. Xuejun JIANG is an Associate Professor in the Department of Statistics and Data Science at SUSTech, specializing in mathematical statistics, likelihood inference, and data science.</p> 01 eng 08 334 03 01 20 Mathematics;statistics;probability;Bayer;data science 10 2011 MAT029000 29 CLIL3056 01 510 05 03 00 <p>Mathematical Statistics is a comprehensive undergraduate textbook developed from the authors’ 18 years of teaching experience at The University of Hong Kong (HKU) and Southern University of Science and Technology (SUSTech). Tailored for undergraduates in Statistics, Data Science and Big Data Technology, as well as graduate students in engineering-related fields, it covers core topics of mathematical statistics with logical rigor—from foundational probability theory to point estimation, interval estimation, hypothesis testing, and key concepts like sufficient statistics and Fisher information. What sets it apart is the inclusion of unique content rarely found in standard textbooks: Inverse Bayes Formulae, the Definition of Valid Categorical Distribution, and a Unified Expectation Technique, bridging theoretical depth with practical relevance for real-world data science applications.</p><p>Distinctive features of this book include:</p><p>1. Innovative Warp-Weft Dual Structure: In addition to the traditional chapter-section “Warp” framework, the book introduces a self-contained “Weft” thread, resulting in a concise and lucid overall structure. This design enables readers to quickly grasp core concepts, key knowledge points, and challenging topics even before completing the book, thereby streamlining the organization of information.</p><p>2. Motivation-Driven Conceptualization: When introducing fundamental concepts (e.g., score functions, Cramér-Rao inequality, confidence intervals), the book emphasizes the underlying motivation—the rationale and practical value behind each concept—to promote genuine understanding other than rote memorization.</p><p>3. Dual Function as Textbook and Presentation: Combining the rigor of a traditional textbook with the clarity of classroom slides, the electronic PDF version can be used directly for teaching. Instructors save preparation time by adopting it as-is or adapting it with their own insights.</p><p>4. Comprehensive Teaching Resources: The authors offer complete English-language supplementary materials, including a sample syllabus, teaching plan, ten tutorials, five assignments with solutions, and 100 additional practice problems—providing structured support for both instructors and students.</p> 02 00 <p>This book covers core topics of mathematical statistics with logical rigor—from foundational probability theory to point estimation, interval estimation, hypothesis testing, and key concepts like sufficient statistics and Fisher information.</p> 04 00 <p>See 'Complements'</p> 21 00 06 01 https://laboutique.edpsciences.fr/product/1547/9782759839490/mathematical-statistics 01 00 03 02 https://laboutique.edpsciences.fr/system/product_pictures/data/009/983/538/original/9782759839490-Mathematical_Statistics_couv-sofedis.jpg 17 14 20260123T095709+0100 01 P15 EDP Sciences & Science Press 01 01 P15 EDP Sciences & Science Press 04 11 00 20260203 01 00 20260203 19 00 20260203 2026 06 3052868830012 01 WORLD 13 03 9782759839483 15 9782759839483 WORLD 08 EDP Sciences & Science Press 04 01 00 20260203 03 01 D1 EDP Sciences 20 04 05 01 02 1 00 84.99 01 5.50 4.43 EUR 04 06 01 02 1 00 297.99 01 5.50 4.43 EUR 01 04 06 01 02 1 00 327.99 01 5.50 17.10 USD 01